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Senior Machine Learning Ops Engineer Jobs in Dallas, TX

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

Veho

Senior Machine Learning Platform Engineer

Dallas, TX · On-site

$103K - $142K/yr

The Senior Machine Learning Platform Engineer will work alongside data scientists and software engineers to create and maintain ML infrastructure, ensuring the deployment and performance of models in ...

Nexxen

Senior Machine Learning Engineer, AdTech

Dallas, TX · On-site +1

$180K - $220K/yr

Sr. Machine Learning Engineer Flexible advertising, unified by data. Nexxen empowers advertisers, agencies, publishers, and broadcasters around the world to utilize data and advanced TV in the ways ...

Samprasoft

Machine Learning Engineer

Roanoke, TX

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Optimum

Sr Machine Learning Engineer

Plano, TX · On-site

$97K - $134K/yr

Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems leveraging AI and/or ML principles as needed to create those solutions. MLEs will take requests from ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · On-site +1

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine capabilities across the organization. You will work closely ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · Remote

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine capabilities across the organization. You will work closely ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine capabilities across the organization. You will work closely ...

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

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All JobsMachine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer Jobs in Dallas, TX

Senior Machine Learning Ops Engineer information

See Dallas, TX salary details

$58.9K

$125.2K

$181.5K

How much do senior machine learning ops engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for senior machine learning ops engineer in Dallas, TX is $125,194.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $142,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Ops Engineer, and why are they important?

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by Senior Machine Learning Ops Engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What are Senior Machine Learning Ops Engineers?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.
What are popular job titles related to Senior Machine Learning Ops Engineer jobs in Dallas, TX? For Senior Machine Learning Ops Engineer jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Ops Engineer jobs in Dallas, TX look for? The top searched job categories for Senior Machine Learning Ops Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Senior Machine Learning Ops Engineer jobs? Cities near Dallas, TX with the most Senior Machine Learning Ops Engineer job openings:
Senior Machine Learning Ops Engineer jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Ascentt

Plano, TX • On-site

$100K - $137K/yr

Full-time

Posted 8 days ago

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring passionate builders to shape the future of industrial intelligence.
Job Title: Senior Machine Learning Engineer
Location: Ann Arbor, Michigan
Experience Level: 7+ Years
Department: Data Science / Engineering
Employment Type: Full-time
About the Role:
We are looking for an experienced Senior Machine Learning Engineer with deep expertise in statistical and machine learning techniques, large-scale data processing, and model deployment in cloud environments. The ideal candidate will be a self-starter with strong problem-solving skills and hands-on experience in building and deploying ML models using big data technologies like PySpark and cloud platforms like Amazon SageMaker.
Key Responsibilities:
  • Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.
  • Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.
  • Apply a wide range of statistical, machine learning, and deep learning techniques, including but not limited to regression, classification, clustering, time-series forecasting, and NLP.
  • Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.
  • Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment.
  • Collaborate closely with data engineers, data scientists, and product teams to integrate models with business workflows.
  • Monitor and improve model performance, scalability, and reliability in production.
  • Contribute to setting up and maintaining the ML environment and tooling (including environment configuration, CI/CD pipelines for ML, model versioning, etc.).

Required Qualifications:
  • 7+ years of experience in machine learning, data science, or related fields.
  • Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
  • Hands-on experience with PySpark for big data processing and model development.
  • Proficient in building models on large-scale datasets (terabytes to petabytes).
  • Solid understanding of statistical analysis, probability, hypothesis testing, and experimental design.
  • Experience with Amazon SageMaker (or similar cloud-based ML platforms).
  • Strong knowledge of ML Ops practices including version control, model monitoring, and retraining strategies.
  • Familiarity with containerization (Docker) and CI/CD practices for ML projects is a plus.
  • Excellent communication skills and the ability to clearly explain complex concepts to non-technical stakeholders.

Preferred Qualifications:
  • Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
  • Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
  • Prior experience in domains like Manufacturing, finance, healthcare, or e-commerce is a plus.

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